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尝试使用引用数据帧从数据帧返回记录

pandas python

Stacey · 技术社区 · 7 年前

DeptTemplate )其中的.head()如下所示:

       Name     Status  Status change date   Product
0       Bob    CURRENT                 NaN   Pencils
1     Steve    CURRENT                 NaN      Pens
2   Heather NEW JOINER          02/08/2018     Paper
3     Lizzy NEW JOINER          06/02/2018      Pens
4     Ralph       LEFT                 NaN     Paper

我正在尝试识别并返回具有非“当前”状态且没有状态更改日期的记录的所有信息。

 def checkStatusChangeDate(DeptTemplate,filename,filepath, referencePeriodStartDate, referencePeriodEndDate,writer):
        #This code checks if a status is not current that there is a status change date attached

        test = DeptTemplate[DeptTemplate.Status != "CURRENT"]

        pd.to_datetime(test['Status change date'])

        test['Status change date'].dt.strftime('%d/%m/%Y')   

        statusError = test['Status change date'] == 'NaT'

        finalError = DeptTemplate.loc[statusError['Status change date']]

我首先确定任何不是“当前”的记录。然后,我从这个子集中识别出任何没有状态更改日期的记录。我的结局是 statusError

4    False

我遇到的问题是,通过引用 状态错误 原始数据帧 脱模板

我正在尝试使用:

finalError = DeptTemplate.loc[statusError['Status change date']]

finalError = DeptTemplate[statusError['Status change date']]

但不能让整个记录在 finalError 数据帧

终结者 数据帧看起来像:

       Name     Status  Status change date   Product
4     Ralph       LEFT                 NaN     Paper

2 回复 | 直到 7 年前

user3471881 7 年前

你就快到了,但你正试着切掉你的原作 DataFrame 数据帧

步骤1:设置布尔掩码

not_current = df['STATUS'] != 'CURRENT'

no_date_change = df['Status change date'].isnull()

第二步:使用口罩

df[not_current & no_date_change]

Lukas Humpe 7 年前

如果我理解正确:您希望找到一个不包含更改日期和当前状态的记录,然后将所有其他记录返回到。因此,如果有其他条目为拉尔夫举例来说,你想得到他们以及。

我的解决方案是:

import pandas as pd 


data = {"Name":["Bob","Steve","Heather","Lizzy","Ralph","Ralph","Ralph"],
    "Status":["CURRENT","CURRENT","NEW JOINER","NEW JOINER","LEFT","CURRENT","CURRENT"],
    "Status change date": ["","","02/08/2018","06/02/2018","","06/02/2018","06/02/2018"],
    "Product":["Pencils","Pens","Paper","Pens","Paper","Pencils","Pens"]}

df = pd.DataFrame(data)

df["Status change date"]=pd.to_datetime(df["Status change date"])

df.head()
      Name      Status Status change date  Product
0      Bob     CURRENT                NaT  Pencils
1    Steve     CURRENT                NaT     Pens
2  Heather  NEW JOINER         2018-02-08    Paper
3    Lizzy  NEW JOINER         2018-06-02     Pens
4    Ralph        LEFT                NaT    Paper
5    Ralph     CURRENT         2018-06-02  Pencils
6    Ralph     CURRENT         2018-06-02     Pens

获取不包含当前状态和状态更改日期的所有条目:

finalError = df[(df["Status"]!="CURRENT") & (df["Status change date"].isnull())]

finalError.head()

    Name Status Status change date Product
4  Ralph   LEFT                NaT   Paper

df[df["Name"]==finalError["Name"].any()]

    Name   Status Status change date  Product
4  Ralph     LEFT                NaT    Paper
5  Ralph  CURRENT         2018-06-02  Pencils
6  Ralph  CURRENT         2018-06-02     Pens